def cmdline_simulate(args):
print 'Simulating'
for arg, arg_value in vars(args).items():
print arg, arg_value
from neurounits import NeuroUnitParser, MQ1
from neurounits.nineml_fe.nineml_fe_utils import get_src_9ml_files
# Load from all the include directories, but only add files once
# to prevent duplicate entries in the library_manager
#src_files = []
#for incl_path in args.include:
# assert os.path.exists(incl_path)
# # Add all the files in a directory:
# if os.path.isdir(incl_path):
# new_files = sorted([ os.path.abspath(fname) for fname in glob.glob(incl_path+'/*.9ml') ] )
# for fname in new_files:
# if not fname in src_files:
# src_files.append(fname)
# # Add an individual file:
# elif os.path.isfile(incl_path):
# if not incl_path in src_files:
# src_files.append(incl_path)
src_files = get_src_9ml_files(args)
# Read all the input files:
library_manager = NeuroUnitParser.Parse9MLFiles(filenames=src_files)
# Get the component:
component = library_manager.get(args.component)
component.summarise()
# Get the start and end times:
t_end = NeuroUnitParser.QuantitySimple(args.endt)
assert t_end.is_compatible(MQ1('1s').units)
t_end = t_end.float_in_si()
dt = NeuroUnitParser.QuantitySimple(args.dt)
assert dt.is_compatible(MQ1('1s').units)
dt = dt.float_in_si()
# OK lets simulate!
res = component.simulate(times=np.arange(0, t_end, dt), )
print 'Simulating'
for arg, arg_value in vars(args).items():
print arg, arg_value
# and plot:
res.auto_plot()
# Shall we pop up?
if args.show_plot:
pylab.show()
print 'Simulating'
for arg, arg_value in vars(args).items():
print arg, arg_value
def cmdline_summarise(args):
import mredoc
print 'Summarise'
from neurounits import NeuroUnitParser, MQ1
from neurounits.nineml_fe.nineml_fe_utils import get_src_9ml_files
src_files = get_src_9ml_files(args)
# Read all the input files:
library_manager = NeuroUnitParser.Parse9MLFiles(filenames=src_files)
print args.what
if not args.what:
objs = list(library_manager.objects)
else:
objs = [ library_manager.get(name) for name in args.what ]
summaries = []
for o in objs:
print 'Summarising:', repr(o)
summaries.append( o.to_redoc() )
summary_obj = mredoc.Section(